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Culture-Oriented Science and technology (CoST), International Conference on

作者： Chaoyu Hu Shilei Bai Mengfei Zhang School of Information and Communication Engineering Communication University of China Beijing China Beijing Key Laboratory of Modern Entertainment Technology Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Oral history involves conveying experienced events through spoken narratives, typically preserved and later studied by converting spoken language into text. Named entity recognition (NER) is the recognition of meaningful named entities in text, such as person names, locations, organizations, etc. Conducting NER research on oral history text is significant as it not only facilitates the verification of named entities by researchers but also allows for the extraction of key information from texts through named entities. By collecting oral history corpus, we establish an oral history text dataset, manually annotating all texts with six entity labels and repeatedly verifying them manually. Utilizing the concept of machine reading comprehension (MRC), a semantic fusion module was added, integrating label information into text information using a cross-attention mechanism, and decoding the corresponding entity labels through span decoding. The final model performs well on the oral history text dataset and also showed good performance on general Chinese datasets.

关键词： Costs Text recognition Semantics Named entity recognition Organizations Decoding History

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Roaming in the concert hall: a customized interactive immersive system for professional musicians and appreciators 24

Roaming in the concert hall: a customized interactive immers...

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24th International Congress on Acoustics, ICA 2022

作者： Liu, Junzhe Liu, Jingyu Zhu, Jiaxing Li, Zijin State Key Laboratory of Media Convergence and Communication Communication University of China China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Communication University of China China Beijing Key Laboratory of Modern Entertainment Technology Communication University of China China School of Information and Communication Engineering Communication University of China China School of Architecture Tianjin University China Department of Musicology China Conservatory of Music China AI music and Music Information Technology Department Central Conservatory of Music China

Virtual concerts have become an emerging form of music performance, and it casts a perspective on the development and exploration of real-time interactive virtual spaces as well as the creation of digital twins. This paper introduces a customizable interactive immersive concert hall system, which can meet the diverse needs of different roles such as audiences, musicians, conductors and audio engineers. It supports switching between different concert hall scenes, changing the placement of orchestra, adjusting instrument volume, and listening to selected instrument ensembles while performing in the concert hall. The system also supports real-time switching between different music pickup types and microphone frequency responses. The system simulates the architectural acoustic environment of outstanding concert halls around the world, and is enabled with real-time auralization. © ICA *** rights reserved

关键词： Concert Hall Acoustic Simulation Interactive Immersive Acoustic Space Real-Time Auralization

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NURBS Modeling and Curve Interpolation Optimization of 3D Graphics

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Computers, Materials & Continua 2021年第2期66卷 1799-1811页

作者： Hao Zhu Mulan Wang Kun Liu Weiye Xu School of Information and Communication Engineering Nanjing Institute of TechnologyNanjing211167China Jiangsu Key Laboratory of Advanced Numerical Control Technology Nanjing Institute of TechnologyNanjing211167China Department of informatics University of LeicesterLeicesterLE17RHUK

In order to solve the problem of complicated Non-Uniform Rational B-Splines(NURBS)modeling and improve the real-time performance of the high-order derivative of the curve interpolation process,the method of NURBS modeling based on the slicing and layering of triangular mesh is *** research and design of NURBS curve interpolation are carried out from the two aspects of software algorithm and hardware *** on the analysis of the characteristics of traditional computing methods with Taylor series expansion,the Adams formula and the Runge-Kutta formula are used in the NURBS curve interpolation process,and the process is then optimized according to the characteristics of NURBS *** can ensure accuracy,and avoid the calculation of higher-order ***,the hardware modules for the Adams and Runge-Kutta formulas are designed by using the parallel hardware construction technology of Field Programmable Gate Array(FPGA)*** parallel computing process using FPGA is compared with the traditional serial computing process using *** and experimental results show that this scheme can improve the computational speed of the system and that the algorithm is feasible.

关键词： NURBS modeling interpolation Adams Runge-Kutta FPGA

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Benchmarking Semantic communications for Image Transmission Over MIMO Interference Channels

arXiv

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arXiv 2024年

作者： Wang, Yanhu Guo, Shuaishuai Dong, Anming Zhao, Hui School of Control Science and Engineering Shandong Key Laboratory of Wireless Communication Technologies Shandong University Jinan250061 China The School of Computer Science and Technology Qilu University of Technology Jinan250353 China The Communication Systems Department EURECOM Sophia Antipolis 06410 France

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input multiple-output (MIMO) interference channels, where we propose an interference-robust semantic communication (IRSC) scheme. This scheme involves the development of transceivers based on neural networks (NNs), which integrate channel state information (CSI) either solely at the receiver or at both transmitter and receiver ends. Moreover, we establish a composite loss function for training IRSC transceivers, along with a dynamic mechanism for updating the weights of various components in the loss function to enhance system fairness among users. Experimental results demonstrate that the proposed IRSC scheme effectively learns to mitigate interference and outperforms baseline approaches, particularly in low signal-to-noise (SNR) regimes. © 2024, CC BY.

关键词： Channel state information

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Satellite Power System Anomaly Detection based on Spatio-Temporal Uncertainty Fusion

Satellite Power System Anomaly Detection based on Spatio-Tem...

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Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： Zhipeng Wang Yanjiao Gao Jingyue Pang Yuchen Song Yu Peng School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin China School of Artificial Intelligence Chongqing Technology and Business University Chongqing China

Satellites have been widely used for military and civil applications. The power system is critical for the satellite’s operating safety. However, satellite power system anomaly monitoring is faced with challenges like large amounts of data, insufficient anomaly samples, and complex operating conditions. To address these challenging issues, this paper proposes a data-driven anomaly detection method that fuses the time-related historical data and spatial-associated sub-system monitor data. Firstly, the probabilistic prediction model is used to establish the prediction model based on time and space The corresponding prediction uncertainties of the temporal and spatial models are quantitatively represented. Then, the stochastic distribution model is introduced to fuse the two uncertainties to obtain the predicted mean value and fusion uncertainty of the current power system state. The mean value is taken as the expected result of the state, and the fused uncertainty interval is taken as the threshold of abnormal judgment to realize the detection of the abnormal condition. The telemetry data of the actual satellite power system are used for experimental and comparative analysis. The results show that the false negative rate of anomaly detection results can be effectively reduced, and the detection accuracy can be improved through the fusion of spatio-temporal uncertainty.

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Recent patents for the motorized spindle preload mechanism

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Recent Patents on Mechanical engineering 2021年第3期14卷 329-341页

作者： Dai, Ye Wen, Wan-Jian Xuan, Li-Yu Yu, Xiao-Yang Wang, Gang Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China School of College of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technolo-gy Harbin150080 China Ningbo Skync Five Axis Numerical Control Tech Co. Ltd Yuyao315400 China

Background: The motorized spindle preload technology is one of the motorized spindle key technologies, and adjusting the preload according to the working conditions can effectively improve the dynamic performance of the motorized spindle and enhance the machining accuracy. Objectives: Review the preload mechanism development, introduce various preload mechanisms, and show research status in recent years. Then to explore and predict the future development of preload technology through the analysis of the overall preload mechanism. Methods: Search for different kinds of patents and literature about spindle preload structure in recent years. Through structural research and comparison with the traditional preload mechanism, to review the structure principle of various preload mechanisms at the present stage, then shown the advantages and disadvantages of each structure. Result: According to the patents and research of the preload mechanism in recent years, classification introduced the piezoelectric ceramic preload device, electromagnetic preload device, and hydraulic preload device, and so on. Introduce their advantages and existing problems in detail, then comprehensively compare the advantages and disadvantages of various mechanisms in control and mechanism. Finally, discuss the prospects and development directions of preload technology. Conclusion: With the further development of technology, high-precision products have higher requirements for machine tools, such as low latency, low heat generation, high efficiency, and long life. People use electromagnetic force, air pressure, hydraulic pressure, and other methods, to control the magnitude of the preload, maintain the performance of the motorized spindle at a high level. Compared with the traditional quantitative preload, their applicable working conditions are more extensive and accuracy is higher. However, various new preload methods still have certain shortcomings and need further improvement. © 2021 Bentham Sci

关键词： Machine tools

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Cognitive Jammer Time Resource Scheduling With Imperfect Information Via Fuzzy Q-Learning

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Gan, Linchuan Xiong, Kui Liao, Maosen Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China UESTC Shenzhen Institute for Advanced Study Shenzhen518038 China

Effective strategy generation of the jammer with inaccurate or undetermined information for combating the radar system is a challenging problem and the relevant research is scarce in existing work. This paper aims at exploring this promising topic and proposing a transmitting time slots scheduling strategy generation method for the cognitive jammer with imperfect time-matching information based on fuzzy reinforcement learning. First, the interaction between the jammer and environment is modeled as a Markov decision process (MDP) with uncertain state and continuous action, in which the goal of the jammer in interaction is to maximize accumulated discount pulse transmitting time slot jamming probability. Then, the uncertain pulse repeat intervals (PRIs) of the radar signal is inferred using the fuzzy inference system (FIS), where the inferred reward is evaluated by the correntropy of the inferred radar PRI and the previously measured one, thus presenting the fuzzy Q-learning based time scheduling (TSFQL) algorithm. Finally, numerical simulations in typical scenarios are performed to illustrate the effectiveness and superiority of the TSFQL algorithm over conventional methods. © 1965-2011 IEEE.

关键词： Markov processes

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Research on Multi - Target Data Association and Location Algorithm Based on Passive Multi - Sensor System 18

Research on Multi - Target Data Association and Location Alg...

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18th International Computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2021

作者： Siyi, Yao Jianliang, Xu Weiguo, Shen Li, Wang Wanchun, Li School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

ISBN: (纸本)9781665413640

In this paper, the multi-target positioning research is carried out on the basis of a passive multi-sensor reconnaissance system, which requires an algorithm to solve the problem of multi-target data association and positioning in the presence of false alarms and missed detections (also named non-ideal). This paper proposes a new data association and localization algorithm. This new algorithm adopts the method of hierarchical association of data, achieves data association through coarse association and fine association, and finally deletes redundant targets through backtracking. The simulation results show the effectiveness and stability of the algorithm. © 2021 IEEE.

关键词： Data association Multi-target Non-ideal Passive multi-sensor

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Machine-learning-based detection for quantum hacking attacks on continuous-variable quantum-key-distribution systems

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Physical Review A 2023年第6期107卷 062422-062422页

作者： Chao Ding Shi Wang Yaonan Wang Zijie Wu Jingtao Sun Yiyu Mao College of Electrical and Information Engineering Hunan University Changsha 410082 China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha 410082 China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha 410114 China

Continuous-variable quantum key distribution (CVQKD) is a mature technology that can theoretically provide an unconditional security guarantee. However, a practical CVQKD system may be vulnerable to various quantum hacking attacks due to imperfect devices and insufficient assumptions. In this paper, we propose a universal defense strategy called a machine-learning-based attack detection scheme (MADS). Leveraging the combined advantages of density-based spatial clustering of applications with noise (DBSCAN) and multiclass support vector machines (MCSVMs), MADS demonstrates remarkable effectiveness in detecting quantum hacking attacks. Specifically, we first establish a set of attack-related features to extract feature vectors. These vectors are then utilized as input data for DBSCAN to identify and remove any noise or outliers. Finally, the trained MCSVMs are employed to classify and predict the processed data. The predicted results can immediately determine whether or not to generate a final secret key. Simulation results show that the proposed MADS can efficiently detect most quantum hacking attacks and revise the overestimated secret key rates caused by a CVQKD system without any defense strategy to obtain a tighter security bound.

关键词： Quantum cryptography

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Dunhuang murals image inpainting method based on fusion classification pre-training model

Dunhuang murals image inpainting method based on fusion clas...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Hui Ren Chengya Zhang Ke Sun Chenyu Ye School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Audiovisual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China Beijing Key Laboratory of Modern Performing Arts Technology Beijing China School of Engineering and Applied Science University of Pennsylvania PA USA

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Murals are an important part of China’s cultural heritage. Because of their age, Dunhuang murals have suffered from discoloration, fading and damage. With the development of computer image restoration technology, digital image processing provides strong support for mural restoration. Although there are many research results in the field of ancient mural images, there is no pre-trained model based on ancient mural images available for migration. There is a method for Dunhuang murals image restoration based on Generative Adversarial Network (GAN) with improved ResNet50 structure as an encoder in the generator. This research result proposes a generative adversarial network model with a parallel double convolutional extraction of deep features for the generator, combined with a ternary heterogeneous joint discriminator. On this basis, this paper proposes a binary classification task to distinguish ancient mural images from modern natural style images, so that the model pre-learns features such as color, texture, and structure of mural images, which are inputted into the restoration network as a priori information, in order to achieve the effect of reducing the probability of incomplete restoration of the model, and better generalization ability. The experimental results show that the method proposed in this paper has an overall improvement in the evaluation indexes such as Peak Signal to Noise Ratio(PSNR) and Structural Similarities(SSIM) when compared with other methods, and the restored images are more in line with human subjective vision, which proves the validity of the method.

关键词： Training Uncertainty Noise Maintenance engineering Generative adversarial networks Feature extraction Generators

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